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\begin{abstract}
\it{
The World Wide Web provides a vast amount of information aimed to suit the interests of any user requesting information. Current search engines are tailored to return search results that are most relevant to the query term received as input. However, often times the user is interested in information that a query cannot easily describe. Search engine results are also often dominated by temporally recent information. Consider the case where a user is interested in all events that relate to a person during their lifetime, essentially a timeline for a given person entity. However, there is no direct way to query a search engine for all of the events in a person's lifetime. Manual timelines exist on the Web and are readily accessible, however, they often do not provide a sufficient or complete amount of information, nor are they always current.

ChronoSearch aims to solve this problem by automatically constructing a timeline related to a person entity in a dynamic fashion. This is done by extracting both temporal and entity specific information from input web pages that could be generated by querying a search engine for the provided entity. The temporal and entity information is then associated to produce event descriptions which are then ordered by date and displayed to the user. ChronoSearch aims to outperform existing manually built timelines on the Web in terms of the comprehensiveness and preciseness of the events that are contained in the generated results.

The evaluation of the ChronoSearch system shows that it is able to perform as well, if not better, in terms of recall of events when compared to existing manual timelines on the Web. The evaluation also indicates initial success in improving the precision of the results via removal of duplicate events and input cleansing. 

The main contribution of this work for the research community is a unique event and temporal information extraction approach applied to the Web. To our knowledge, ChronoSearch is the first system that attempts to generate timelines from all categories of web pages. The approach demonstrates that redundancy present on the Web can be utilized to focus on only the strongest extraction signals. It also provides a working prototype, and an evaluation methodology for automatically generated timelines.
}
\end{abstract}



